Using an Architecture Description Language to Model a Large- Scale Information System – An Industrial Experience Report

An organisation that had developed a large Information System wanted to embark on a programme of significant evolution for the system. As a precursor to this, it was decided to create a comprehensive architectural description. T his undertaking faced a number of challenges, including a low general awareness of software modelling and software architecture practices . The approach taken for this project included the definition of a simple, specific, architecture description language. This paper describes the experiences of the project and the ADL created as part of it

Towards a More Representative Definition of Cyber Security

In recent years, ‘Cyber Security’ has emerged as a widely-used term with increased adoption by practitioners and politicians alike. However, as with many fashionable jargon, there seems to be very little understanding of what the term really entails. Although this is may not be an issue when the term is used in an informal context, it can potentially cause considerable problems in context of organizational strategy, business objectives, or international agreements. In this work, we study the existing literature to identify the main definitions provided for the term ‘Cyber Security’ by authoritative sources. We then conduct various lexical and semantic analysis techniques in an attempt to better understand the scope and context of these definitions, along with their relevance. Finally, based on the analysis conducted, we propose a new improved definition that we then demonstrate to be a more representative definition using the same lexical and semantic analysis techniques

Measuring energy footprint of software features

Abstract—With the proliferation of Software systems and the rise of paradigms such the Internet of Things, Cyber- Physical Systems and Smart Cities to name a few, the energy consumed by software applications is emerging as a major concern. Hence, it has become vital that software engineers have a better understanding of the energy consumed by the code they write. At software level, work so far has focused on measuring the energy consumption at function and application level. In this paper, we propose a novel approach to measure energy consumption at a feature level, cross-cutting multiple functions, classes and systems. We argue the importance of such measurement and the new insight it provides to non-traditional stakeholders such as service providers. We then demonstrate, using an experiment, how the measurement can be done with a combination of tools, namely our program slicing tool (PORBS) and energy measurement tool (Jolinar)

Data Center Energy Demand: what got us here won't get us there!

Given environmentalism's rising tide and increasing energy prices and IT workloads, architects must determine whether they can continue designing systems without considering energy and power efficiency

Achieving Model Completeness for Hierarchally Structured Activities of Daily Life

Being able to recognise everyday activities of daily life provides the opportunity of tracking functional decline among elderly people who suffer from Alzheimer’s disease. This paper describes an approach that has been developed for recognising activities of daily life based on a hierarchal structure of plans. While it is logical to envisage that the most common activities will be modelled within a library of plans, it can be impossible to imagine that the library contains plans for every possible hierarchal activity. In order to generalise the activity recognition capability outside the framework of the core activities constructed to support recognition, decision trees are constructed using a well - known induction algorithm during a train period. The motivation of this work is to allow people with Alzheimer’s disease to have additional years of independent living before the disease reaches a stage where it becomes incurable

A Semantic Rule-based Approach Supported by Process Mining for Personalised Adaptive Learning

Currently, automated learning systems are widely used for educational and training purposes within various organisations including, schools, universities and further education centres. There has been a big gap between the extraction of useful patterns from data sources to knowledge, as it is crucial that data is made valid, novel, potentially useful and understandable. To meet the needs of intended users, there is requirement for learning systems to embody technologies that support learners in achieving their learning goals and this process don’t happen automatically. This paper propose a novel approach for automated learning that is capable of detecting changing trends in learning behaviours and abilities through the use of process mining techniques. The goal is to discover user interaction patterns within learning processes, and respond by making decisions based on adaptive rules centred on captured user profiles. The approach applies semantic annotation of activity logs within the learning process in order to discover patterns automatically by means of semantic reasoning. Therefore, our proposed approach is grounded on Semantic Modelling and Process Mining techniques. To this end, it is possible to apply effective reasoning methods to make inferences over a Learning Process Knowledge-Base that leads to automated discovery of learning patterns or behaviour

A survey on cost-effective context-aware distribution of social data streams over energy-efficient data centres

Social media have emerged in the last decade as a viable and ubiquitous means of communication. The ease of user content generation within these platforms, e.g. check-in information, multimedia data, etc., along with the proliferation of Global Positioning System (GPS)-enabled, always-connected capture devices lead to data streams of unprecedented amount and a radical change in information sharing. Social data streams raise a variety of practical challenges, including derivation of real-time meaningful insights from effectively gathered social information, as well as a paradigm shift for content distribution with the leverage of contextual data associated with user preferences, geographical characteristics and devices in general. In this article we present a comprehensive survey that outlines the state-of-the-art situation and organizes challenges concerning social media streams and the infrastructure of the data centres supporting the efficient access to data streams in terms of content distribution, data diffusion, data replication, energy efficiency and network infrastructure. We systematize the existing literature and proceed to identify and analyse the main research points and industrial efforts in the area as far as modelling, simulation and performance evaluation are concerned

Integration operators for generating RDF/OWL-based user defined mediator views in a grid environment

Research and development activities relating to the grid have generally focused on applications where data is stored in files. However, many scientific and commercial applications are highly dependent on Information Servers (ISs) for storage and organization of their data. A data-information system that supports operations on multiple information servers in a grid environment is referred to as an interoperable grid system. Different perceptions by end-users of interoperable systems in a grid environment may lead to different reasons for integrating data. Even the same user might want to integrate the same distributed data in various ways to suit different needs, roles or tasks. Therefore multiple mediator views are needed to support this diversity. This paper describes our approach to supporting semantic interoperability in a heterogeneous multi-information server grid environment. It is based on using Integration Operators for generating multiple semantically rich RDF/OWL-based user defined mediator views above the grid participating ISs. These views support different perceptions of the distributed and heterogeneous data available. A set of grid services are developed for the implementation of the mediator views

Economic Valuation for Information Security Investment: A Systematic Literature Review

Research on technological aspects of information security risk is a well-established area and familiar territory for most information security professionals. The same cannot be said about the economic value of information security investments in organisations. While there is an emerging research base investigating suitable approaches measuring the value of investments in information security, it remains difficult for practitioners to identify key approaches in current research. To address this issue, we conducted a systematic literature review on approaches used to evaluate investments in information security. Following a defined review protocol, we searched several databases for relevant primary studies and extracted key details from the identified studies to answer our research questions. The contributions of this work include: a comparison framework and a catalogue of existing approaches and trends that would help researchers and practitioners navigate existing work; categorisation and mapping of approaches according to their key elements and components; and a summary of key challenges and benefits of existing work, which should help focus future research efforts